Modeling and prediction of binding affinities between the human amphiphysin SH3 domain and its peptide ligands using genetic algorithm-Gaussian processes

In this article, we discuss the application of the Gaussian process (GP) and other statistical methods (PLS, ANN, and SVM) for the modeling and prediction of binding affinities between the human amphiphysin SH3 domain and its peptide ligands. Divided physicochemical property scores of amino acids, involving significant hydrogen bond, electronic, hydrophobic, and steric properties, was used to characterize the peptide structures, and quantitative structure-affinity relationship models were then constructed by PLS, ANN, SVM, and GP coupled with genetic algorithm-variable selection. The results show that: (i) since the significant flexibility and high complexity possessed in polypeptide structures, linear PLS method was incapable of fulfilling a satisfying behavior on SH3 domain binding peptide dataset; (ii) the overfitting involved in training process has decreased the predictive power of ANN model to some extent; (iii) both SVM and GP have a good performance for SH3 domain binding peptide dataset. Moreover, by combining linear and nonlinear terms in the covariance function, the GP is capable of handling linear and nonlinear-hybrid relationship, and which thus obtained a more stable and predictable model than SVM. Analyses of GP models showed that diversified properties contribute remarkable effect to the interactions between the SH3 domain and the peptides. Particularly, steric property and hydrophobicity of P(2), electronic property of P(0), and electronic property and hydrogen bond property of P(-3) in decapeptide (P(4)P(3)P(2)P(1)P(0)P(-1)P(-2)P(-3)P(-4)P(-5)) significantly contribute to the binding affinities of SH3 domain-peptide interactions.     

Electrostatic Interactions in the Binding Pathway of a Transient Protein Complex Studied by NMR and Isothermal Titration Calorimetry

Much of our knowledge of protein binding pathways is derived from extremely stable complexes that interact very tightly, with lifetimes of hours to days. Much less is known about weaker interactions and transient complexes because these are challenging to characterize experimentally. Nevertheless, these types of interactions are ubiquitous in living systems. The combination of NMR relaxation dispersion Carr–Purcell–Meiboom–Gill (CPMG) experiments and isothermal titration calorimetry allows the quantification of rapid binding kinetics for complexes with submillisecond lifetimes that are difficult to study using conventional techniques. We have used this approach to investigate the binding pathway of the Src homology 3 (SH3) domain from the Fyn tyrosine kinase, which forms complexes with peptide targets whose lifetimes are on the order of about a millisecond. Long range electrostatic interactions have been shown to play a critical role in the binding pathways of tightly binding complexes. The role of electrostatics in the binding pathways of transient complexes is less well understood. Similarly to previously studied tight complexes, we find that SH3 domain association rates are enhanced by long range electrostatics, whereas short range interactions are formed late in the docking process. However, the extent of electrostatic association rate enhancement is several orders of magnitudes less, whereas the electrostatic-free basal association rate is significantly greater. Thus, the SH3 domain is far less reliant on electrostatic enhancement to achieve rapid association kinetics than are previously studied systems. This suggests that there may be overall differences in the role played by electrostatics in the binding pathways of extremely stable versus transient complexes.     

Proteome-Wide Inference of Src Homology 3 Domain-Binding Peptides

Src homology 3 (SH3) domain is a versatile protein structure module that participates in mediating various protein?Cprotein binding events by specifically recognizing proline-rich region of diverse plasmatic proteins. Reliable and fast inference of SH3-binding partners over the human proteome are fundamentally important for our understanding of the molecular functions and biological implications underlying SH3-mediated signaling network. Herein, we employ an atom-realistic protocol to perform proteome-wide inference of SH3-binding peptides using the information gained from both the primary sequence of affinity-known peptides and the interaction properties deriving from SH3?Cpeptide complex structures. It is revealed that the binding affinity and specificity of peptides to SH3 domain are co-contributed from electrostatic, steric and hydrophobic effects, and the hydrophobicity and electrostatic property at P₂, P₀ and/or P_?3 play an essential role in determining the binding. In addition, SH3 domain exhibits a broad specificity of recognizing its ligands and thus a large number of protein candidates that might be the potential interacting partners of SH3 domain are extracted from the human proteome, from which several samples are suggested to be the highly promising SH3 binders.     

Ubiquitin binds to and regulates a subset of SH3 domains

SH3 domains are modules of 50-70 amino acids that promote interactions among proteins, often participating in the assembly of large dynamic complexes. These domains bind to peptide ligands, which usually contain a core Pro-X-X-Pro (PXXP) sequence. Here we identify a class of SH3 domains that bind to ubiquitin. The yeast endocytic protein Sla1, as well as the mammalian proteins CIN85 and amphiphysin, carry ubiquitin-binding SH3 domains. Ubiquitin and peptide ligands bind to the same hydrophobic groove on the SH3 domain surface, and ubiquitin and a PXXP-containing protein fragment compete for binding to SH3 domains. We conclude that a subset of SH3 domains constitutes a distinct type of ubiquitin-binding domain and that ubiquitin binding can negatively regulate interaction of SH3 domains with canonical proline-rich ligands.     

Fast and reliable prediction of domain–peptide binding affinity using coarse-grained structure models

Domain–peptide recognition and interaction are fundamentally important for eukaryotic signaling and regulatory networks. It is thus essential to quantitatively infer the binding stability and specificity of such interaction based upon large-scale but low-accurate complex structure models which could be readily obtained from sophisticated molecular modeling procedure. In the present study, a new method is described for the fast and reliable prediction of domain–peptide binding affinity with coarse-grained structure models. This method is designed to tolerate strong random noises involved in domain–peptide complex structures and uses statistical modeling approach to eliminate systematic bias associated with a group of investigated samples. As a paradigm, this method was employed to model and predict the binding behavior of various peptides to four evolutionarily unrelated peptide-recognition domains (PRDs), i.e. human amph SH3, human nherf PDZ, yeast syh GYF and yeast bmh 14-3-3, and moreover, we explored the molecular mechanism and biological implication underlying the binding of cognate and noncognate peptide ligands to their domain receptors. It is expected that the newly proposed method could be further used to perform genome-wide inference of domain–peptide binding at three-dimensional structure level.     

Hierarchy of simulation models in predicting molecular recognition mechanisms from the binding energy landscapes: structural analysis of the peptide complexes with SH2 domains.

Computer simulations using the simplified energy function and simulated tempering dynamics have accurately determined the native structure of the pYVPML, SVLpYTAVQPNE, and SPGEpYVNIEF peptides in the complexes with SH2 domains. Structural and equilibrium aspects of the peptide binding with SH2 domains have been studied by generating temperature-dependent binding free energy landscapes. Once some native peptide-SH2 domain contacts are constrained, the underlying binding free energy profile has the funnel-like shape that leads to a rapid and consistent acquisition of the native structure. The dominant native topology of the peptide-SH2 domain complexes represents an extended peptide conformation with strong specific interactions in the phosphotyrosine pocket and hydrophobic interactions of the peptide residues C-terminal to the pTyr group. The topological features of the peptide-protein interface are primarily determined by the thermodynamically stable phosphotyrosyl group. A diversity of structurally different binding orientations has been observed for the amino-terminal residues to the phosphotyrosine. The dominant native topology for the peptide residues carboxy-terminal to the phosphotyrosine is tolerant to flexibility in this region of the peptide-SH2 domain interface observed in equilibrium simulations. The energy landscape analysis has revealed a broad, entropically favorable topology of the native binding mode for the bound peptides, which is robust to structural perturbations. This could provide an additional positive mechanism underlying tolerance of the SH2 domains to hydrophobic conservative substitutions in the peptide specificity region.     

Bayesian Modeling of the Yeast SH3 Domain Interactome Predicts Spatiotemporal Dynamics of Endocytosis Proteins

SH3 domains are peptide recognition modules that mediate the assembly of diverse biological complexes. We scanned billions of phage-displayed peptides to map the binding specificities of the SH3 domain family in the budding yeast, Saccharomyces cerevisiae. Although most of the SH3 domains fall into the canonical classes I and II, each domain utilizes distinct features of its cognate ligands to achieve binding selectivity. Furthermore, we uncovered several SH3 domains with specificity profiles that clearly deviate from the two canonical classes. In conjunction with phage display, we used yeast two-hybrid and peptide array screening to independently identify SH3 domain binding partners. The results from the three complementary techniques were integrated using a Bayesian algorithm to generate a high-confidence yeast SH3 domain interaction map. The interaction map was enriched for proteins involved in endocytosis, revealing a set of SH3-mediated interactions that underlie formation of protein complexes essential to this biological pathway. We used the SH3 domain interaction network to predict the dynamic localization of several previously uncharacterized endocytic proteins, and our analysis suggests a novel role for the SH3 domains of Lsb3p and Lsb4p as hubs that recruit and assemble several endocytic complexes.     

Diversity in peptide recognition by the SH2 domain of SH2B1

SH2B1 is a multidomain protein that serves as a key adaptor to regulate numerous cellular events, such as insulin, leptin, and growth hormone signaling pathways. Many of these protein‐protein interactions are mediated by the SH2 domain of SH2B1, which recognizes ligands containing a phosphorylated tyrosine (pY), including peptides derived from janus kinase 2, insulin receptor, and insulin receptor substrate‐1 and ?2. Specificity for the SH2 domain of SH2B1 is conferred in these ligands either by a hydrophobic or an acidic side chain at the +3 position C‐terminal to the pY. This specificity for chemically disparate species suggests that SH2B1 relies on distinct thermodynamic or structural mechanisms to bind to peptides. Using binding and structural strategies, we have identified unique thermodynamic signatures for each peptide binding mode, and several SH2B1 residues, including K575 and R578, that play distinct roles in peptide binding. The high‐resolution structure of the SH2 domain of SH2B1 further reveals conformationally plastic protein loops that may contribute to the ability of the protein to recognize dissimilar ligands. Together, numerous hydrophobic and electrostatic interactions, in addition to backbone conformational flexibility, permit the recognition of diverse peptides by SH2B1. An understanding of this expanded peptide recognition will allow for the identification of novel physiologically relevant SH2B1/peptide interactions, which can contribute to the design of obesity and diabetes pharmaceuticals to target the ligand‐binding interface of SH2B1 with high specificity.     

Computational dissection of allosteric inhibition of the SH2 domain of Bcr-Abl kinase by the monobody inhibitor AS25

The deregulated breakpoint cluster region (Bcr)–Abelson tyrosine kinase (Abl) fusion protein represents an attractive pharmacological target for the treatment of chronic myeloid leukemia (CML). The high affinity of monobody AS25 was designed to target the Src homology 2 (SH2) domain of Bcr-Abl, leading to allosteric inhibition of Bcr-Abl through formation of protein–protein interactions. An I164E mutation in the SH2 domain disrupts AS25 binding to the SH2 domain of Bcr-Abl. The detailed mechanisms, however, remain to be unresolved. Here, molecular dynamics (MD) simulations and binding free energy calculations were performed to explore the conformational and energetic differences between the wild-type (WT) complexes of Bcr-Abl SH2 domain and AS25 (SH2^WT–AS25) as well as the mutated complexes (SH2^I164E–AS25). The results revealed that I164E mutation not only caused an increase in the conformational flexibility of SH2–AS25 complexes, but also weakened the binding affinity of AS25 to SH2. The comparative binding modes of SH2-AS25 complexes between WT and the I164E mutant were comprehensively analyzed to unravel the disruption of hydrophobic and hydrogen bonding interactions in the interface of the SH2-AS25 complex triggered by the I164E mutation. The results obtained may help to design the next generation of higher affinity Bcr-Abl SH2-specific peptide inhibitors.     

Conformational Determinants of Phosphotyrosine Peptides Complexed with the Src SH2 Domain

The inhibition of specific SH2 domain mediated protein-protein interactions as an effective chemotherapeutic approach in the treatment of diseases remains a challenge. That different conformations of peptide-ligands are preferred by different SH2 domains is an underappreciated observation from the structural analysis of phosphotyrosine peptide binding to SH2 domains that may aid in future drug design. To explore the nature of ligand binding, we use simulated annealing (SA) to sample the conformational space of phosphotyrosine-containing peptides complexed with the Src SH2 domain. While in good agreement with the crystallographic and NMR studies of high-affinity phosphopeptide-SH2 domain complexes, the results suggest that the structural basis for phopsphopeptide- Src SH2 interactions is more complex than the “two-pronged plug two-hole socket” model. A systematic study of peptides of type pYEEX, where pY is phosphotyrosine and X is a hydrophobic residue, indicates that these peptides can assume two conformations, one extended and one helical, representing the balance between the interaction of residue X with the hydrophobic hole on the surface of the Src SH2 domain, and its contribution to the inherent tendency of the two glutamic acids to form an α-helix. In contrast, a β-turn conformation, almost identical to that observed in the crystal structure of pYVNV bound to the Grb2 SH2 domain, predominates for pYXNX peptides, even in the presence of isoleucine at the third position. While peptide binding affinities, as measured by fluorescence polarization, correlate with the relative proportion of extended peptide conformation, these results suggest a model where all three residues C-terminal to the phosphotyrosine determine the conformation of the bound phosphopeptide. The information obtained in this work can be used in the design of specific SH2 domain inhibitors.     

Structural basis of Robo proline-rich motif recognition by the srGAP1 Src homology 3 domain in the Slit-Robo signaling pathway

The Slit-Robo (sr) GTPase-activating protein (GAPs) are important components in the intracellular pathway mediating Slit-Robo signaling in axon guidance and cell migration. We report the first crystal structure of the srGAP1 SH3 domain at 1.8-A resolution. The unusual side chain conformation of the conserved Phe-13 in the P1 pocket renders the ligand binding pocket shallow and narrow, which contributes toward the low binding affinity. Moreover, the opposing electrostatic charge and the hydrophobic properties of the P3 specificity pocket are consistent with the observed binding characteristics of the srGAP1 SH3 domain to its ligand. Surface plasmon resonance experiments indicate that the srGAP1 SH3 domain interacts with its natural ligand inaCtoN orientation. The srGAP1 SH3 domain can bind to both the CC2 and CC3 motifs in vitro. The N-terminal two acidic residues in the CC3 motif recognition site are necessary for srGAP1 SH3 domain binding. A longer CC3 peptide (CC3-FL) binds with greater affinity than its shorter counterpart, suggesting that the residues surrounding the proline-rich core are important for protein-peptide interactions. Our study reveals previously unknown properties of the srGAP-Robo interaction. Our data provide a structural basis for the srGAP-Robo interaction, consistent with the role of the Robo intracellular domain in interacting with other downstream signaling molecules and mediating versatile and dynamic responses to axon guidance and cell migration cues.     

Exploration of the binding of proton pump inhibitors to human P450 2C9 based on docking and molecular dynamics simulation

Human P450 protein CYP2C9 is one of the major drug-metabolizing isomers, contributing to the oxidation of 16% of the drugs currently in clinical use. To examine the interaction mechanisms between CYP2C9 and proton pump inhibitions (PPIs), we used molecular docking and molecular dynamics (MD) simulation methods to investigate the conformations and interactions around the binding sites of PPIs/CYPP2C9. Results from molecular docking and MD simulations demonstrate that nine PPIs adopt two different conformations (extended and U-bend structures) at the binding sites and position themselves far above the heme of 2C9. The presence of PPIs changes the secondary structures and residue flexibilities of 2C9. Interestingly, at the binding sites of all PPI–CYP2C9 complexes except for Lan/CYP2C9, there are hydrogen-bonding networks made of PPIs, water molecules, and some residues of 2C9. Moreover, there are strong hydrophobic interactions at all binding sites for PPIs/2C9, which indicate that electrostatic interactions and hydrophobic interactions appear to be important for stabilizing the binding sites of most PPIs/2C9. However, in the case of Lan/2C9, the hydrophobic interactions are more important than the electrostatic interactions for stabilizing the binding site. In addition, an interesting conformational conversion from extended to U-bend structures was observed for pantoprazole, which is attributed to an H-bond interaction in the binding pocket, an internal π–π stacking interaction, and an internal electrostatic interaction of pantoprazole.     

Characterization of domain-peptide interaction interface: a case study on the amphiphysin-1 SH3 domain

Many important protein-protein interactions are mediated by peptide recognition modular domains, such as the Src homology 3 (SH3), SH2, PDZ, and WW domains. Characterizing the interaction interface of domain-peptide complexes and predicting binding specificity for modular domains are critical for deciphering protein-protein interaction networks. Here, we propose the use of an energetic decomposition analysis to characterize domain-peptide interactions and the molecular interaction energy components (MIECs), including van der Waals, electrostatic, and desolvation energy between residue pairs on the binding interface. We show a proof-of-concept study on the amphiphysin-1 SH3 domain interacting with its peptide ligands. The structures of the human amphiphysin-1 SH3 domain complexed with 884 peptides were first modeled using virtual mutagenesis and optimized by molecular mechanics (MM) minimization. Next, the MIECs between domain and peptide residues were computed using the MM/generalized Born decomposition analysis. We conducted two types of statistical analyses on the MIECs to demonstrate their usefulness for predicting binding affinities of peptides and for classifying peptides into binder and non-binder categories. First, combining partial least squares analysis and genetic algorithm, we fitted linear regression models between the MIECs and the peptide binding affinities on the training data set. These models were then used to predict binding affinities for peptides in the test data set; the predicted values have a correlation coefficient of 0.81 and an unsigned mean error of 0.39 compared with the experimentally measured ones. The partial least squares-genetic algorithm analysis on the MIECs revealed the critical interactions for the binding specificity of the amphiphysin-1 SH3 domain. Next, a support vector machine (SVM) was employed to build classification models based on the MIECs of peptides in the training set. A rigorous training-validation procedure was used to assess the performances of different kernel functions in SVM and different combinations of the MIECs. The best SVM classifier gave satisfactory predictions for the test set, indicated by average prediction accuracy rates of 78% and 91% for the binding and non-binding peptides, respectively. We also showed that the performance of our approach on both binding affinity prediction and binder/non-binder classification was superior to the performances of the conventional MM/Poisson-Boltzmann solvent-accessible surface area and MM/generalized Born solvent-accessible surface area calculations. Our study demonstrates that the analysis of the MIECs between peptides and the SH3 domain can successfully characterize the binding interface, and it provides a framework to derive integrated prediction models for different domain-peptide systems.     

Autoinhibition of Endophilin in Solution via Interdomain Interactions

Endophilin is a key protein involved in clathrin-mediated endocytosis. Previous computational and experimental work suggested that the N-terminal helix is embedded into the membrane to induce curvature; however, the role of the SH3 domain remains controversial. To address this issue, we performed computer simulations of the endophilin dimer in solution to understand the interaction between the N-BAR and SH3 domains and its effect on biological function. We predict that the helix binds to the SH3 domain through hydrophobic and salt-bridge interactions. This protects the hydrophobic residues on both domains and keeps the SH3 domain near the end of the N-BAR domain, in agreement with previous experimental results. The complex has a binding strength similar to a few hydrogen bonds (13.0 ± 0.6 kcal/mol), and the SH3 domain stabilizes the structure of the N-terminal helix in solution. Electrostatic calculations show a large region of strongly positive electrostatic potential near the N-terminal that can orient the helix toward the membrane and likely embed the helix into the membrane surface. This predicted mechanism suggests that endophilin can select for both curvature and electrostatic potential when interacting with membranes, highlighting the importance of the SH3 domain in regulating the function of endophilin.     

Solution structure of the SH2 domain of Grb2 complexed with the Shc-derived phosphotyrosine-containing peptide.

The solution structure of growth factor receptor-bound protein 2 (Grb2) SH2 complexed with a Shc-derived phosphotyrosine (pTyr)-containing peptide was determined by nuclear magnetic resonance (NMR) spectroscopy. The pTyr binding site of Grb2 SH2 was similar to those of other SH2 domains. In contrast, the amino acid residues C-terminal to pTyr did not form an extended structure because of steric hindrance caused by a bulky side-chain of Trp121 (EF1). As a result, the peptide formed a turn-structure on the surface of Grb2 SH2. The asparagine residue at the pTyr+2 position of the Shc-peptide interacted with the main-chain carbonyl groups of Lys109 and Leu120. The present solution structure was similar to the crystal structure reported for Grb2 SH2 complexed with a BCR-Abl-derived phosphotyrosine-containing peptide. Finally, the structure of Grb2 SH2 domain was compared with those of the complexes of Src and phospholipase C-gamma1 with their cognate peptides, showing that the specific conformation of the peptide was required for binding to the SH2 domains.     

Human collagen II peptide 256–271 preferentially binds to HLA-DR molecules associated with susceptibility to rheumatoid arthritis

 The binding ability of 23 overlapping peptides, all derived from the CB11 fragment of CII, was tested on several HLA-DR molecules associated or not with disease susceptibility. These experiments were performed on a variety of cells expressing different HLA-DR molecules, using both indirect and direct binding assays. The CII (256–271) fragment was shown to bind to a restricted population among which the HLA-DR molecules associated with susceptibility to rheumatoid arthritis. The results also clearly indicate that the binding specificity of CII (256–271), among the DR4 molecules, is controlled by the nature of the HLA-DR molecule β-chain residues 71 and 74, residues previously shown by X-ray crystallography to be involved in the HLA-DR/peptide interaction. The human CII (256–271) peptide is thus likely to play a role in the disease process. Received: 6 May 1998 / Revised: 16 July 1998     

The nature of “masked” and “free” sulfhydryl groups in proteins

The relative amounts of readily titrable (‘free’) SH groups, versus that of SH groups titrable readily only following denaturation (‘masked’) has been shown by Szent-Gyorgyi to vary significantly from normal to cancerous organ tissue. It is important therefore to inquire into the causes of the two forms of protein-borne SH. Of the four suggested mechanisms for the “masking” of protein SH groups, (1) sequestration in hydrophobic regions-whether between chain folds or between agglomerated subunits, (2) local steric hindrance, (3) cyclic hydrogen-bonding to local peptide amino acid residues, or (4) covalent bonding as in thiazolines; the first mechanism, that of sequestration in hydrophobic regions appears from present evidence to be the most likely cause. Various spectroscopic, reaction rate, and entropy arguments are presented and compared leading to this conclusion.     

Quantitative Structure–Activity Relationship Model for Prediction of Protein–Peptide Interaction Binding Affinities between Human Amphiphysin-1 SH3 Domains and Their Peptide Ligands

Protein–protein interaction plays a critical role in signal transduction and many other key biological processes. The present study evaluated four parameters selected from among 554 physiochemical variables of 20 natural amino acids listed in AAindex, namely, hydrophobicity, electronic properties, steric properties, and hydrogen-bond properties. Human amphiphysin-1 Src homology 3 (SH3) domain-binding decapeptides were the object of analysis. A quantitative structure–activity relationship model of the SH3 domain-binding peptides was constructed using multivariate linear regression. The results showed that the four parameters ably characterize the structure of SH3 domain-binding decapeptides, have definitive physicochemical properties and a low level of computational complexity, are accessible, and may be used in integrated prediction models for other protein–peptide interactions.